数据融合中支持隐私保护的完整性动态验证算法

计算机科学 ›› 2013, Vol. 40 ›› Issue (7): 84-88.

数据融合中支持隐私保护的完整性动态验证算法

陈伟,杨龙,于乐

南京邮电大学计算机学院南京210023 江苏省无线传感网高技术研究重点实验室南京210003;南京邮电大学计算机学院南京210023 江苏省无线传感网高技术研究重点实验室南京210003;南京邮电大学计算机学院南京210023 江苏省无线传感网高技术研究重点实验室南京210003

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家自然科学基金(61202353,4)资助

Privacy-preserving Dynamic Integrity-verification Algorithm in Data Aggregation

CHEN Wei,YANG Long and YU Le

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 隐私暴露、信息篡改、虚假数据注入都是无线传感器网络数据融合中面临的严峻挑战,在保护数据隐私性的同时进行完整性验证是数据融合技术研究的热点之一。提出了一种新的支持隐私保护的动态完整性验证算法PDI(Privacy-preserving Dynamic Integrity-verification algorithm),它可以在实现数据隐私保护的基础上侦测到信息被非法篡改。PDI算法使用数据扰动进行数据隐私保护,同时根据现有网络结构动态生成监测节点进行数据的完整性验证,融合过程中篡改过的虚假数据能够更快地被检测并丢弃。仿真实验结果显示,PDI算法可使用较少的通信量和计算量实现隐私保护和完整性验证。

关键词: 无线传感器网络,数据融合,隐私保护,完整性验证,数据扰动中图法分类号TP393-08文献标识码A

Abstract: Privacy exposure,information tampering and false data injection are serious challenges in wireless sensor network data aggregation．How to protect the privacy and integrity of data has become a hot research issue in data aggregation．To detect any malicious data tampering and protect data privacy in data aggregation,a novel Privacy-preserving dynamic Integrity-verification(PDI) algorithm was proposed．The PDI algorithm uses the data is perturbation to protect data privacy．In order to protect the integrity of privacy data,the PDI algorithm generates monitoring nodes between the current aggregator and its parent node depending on the network structure dynamically．Therefore,if the data is tampered by the aggregator,it can be detected at the early stage．The simulation results show that the PDI algorithm can reali-ze privacy preserving and integrity verification with less communication and computation overhead．

Key words: Wireless sensor network,Data aggregation,Privacy preserving,Integrity verification,Data perturbation

陈伟,杨龙,于乐. 数据融合中支持隐私保护的完整性动态验证算法[J]. 计算机科学, 2013, 40(7): 84-88. https://doi.org/

CHEN Wei,YANG Long and YU Le. Privacy-preserving Dynamic Integrity-verification Algorithm in Data Aggregation[J]. Computer Science, 2013, 40(7): 84-88. https://doi.org/

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